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https://issues.apache.org/jira/browse/SPARK-25908?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sean Owen resolved SPARK-25908.
-------------------------------
       Resolution: Fixed
    Fix Version/s: 3.0.0

Issue resolved by pull request 22921
[https://github.com/apache/spark/pull/22921]

> Remove old deprecated items in Spark 3
> --------------------------------------
>
>                 Key: SPARK-25908
>                 URL: https://issues.apache.org/jira/browse/SPARK-25908
>             Project: Spark
>          Issue Type: Task
>          Components: Spark Core, SQL
>    Affects Versions: 3.0.0
>            Reporter: Sean Owen
>            Assignee: Sean Owen
>            Priority: Major
>             Fix For: 3.0.0
>
>
> There are many deprecated methods and classes in Spark. They _can_ be removed 
> in Spark 3, and for those that have been deprecated a long time (i.e. since 
> Spark <= 2.0), we should probably do so. This addresses most of these cases, 
> the easiest ones, those that are easy to remove and are old:
>  - Remove some AccumulableInfo .apply() methods
>  - Remove non-label-specific multiclass precision/recall/fScore in favor of 
> accuracy
>  - Remove toDegrees/toRadians in favor of degrees/radians (SparkR: only 
> deprecated)
>  - Remove approxCountDistinct in favor of approx_count_distinct (SparkR: only 
> deprecated)
>  - Remove unused Python StorageLevel constants
>  - Remove Dataset unionAll in favor of union
>  - Remove unused multiclass option in libsvm parsing
>  - Remove references to deprecated spark configs like spark.yarn.am.port
>  - Remove TaskContext.isRunningLocally
>  - Remove ShuffleMetrics.shuffle* methods
>  - Remove BaseReadWrite.context in favor of session
>  - Remove Column.!== in favor of =!=
>  - Remove Dataset.explode
>  - Remove Dataset.registerTempTable
>  - Remove SQLContext.getOrCreate, setActive, clearActive, constructors
> Not touched yet:
>  - everything else in MLLib
>  - HiveContext
>  - Anything deprecated more recently than 2.0.0, generally



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